Identification of a Three-Biomarker Panel in Urine for Early Detection of Pancreatic Adenocarcinoma

Abstract

Purpose: Noninvasive biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are currently not available. Here, we aimed to identify a set of urine proteins able to distinguish patients with early-stage PDAC from healthy individuals.

Experimental design: Proteomes of 18 urine samples from healthy controls, chronic pancreatitis, and patients with PDAC (six/group) were assayed using GeLC/MS/MS analysis. The selected biomarkers were subsequently validated with ELISA assays using multiple logistic regression applied to a training dataset in a multicenter cohort comprising 488 urine samples.

Results: LYVE-1, REG1A, and TFF1 were selected as candidate biomarkers. When comparing PDAC (n = 192) with healthy (n = 87) urine specimens, the resulting areas under the receiver-operating characteristic curves (AUC) of the panel were 0.89 [95% confidence interval (CI), 0.84-0.94] in the training (70% of the data) and 0.92 (95% CI, 0.86-0.98) in the validation (30% of the data) datasets. When comparing PDAC stage I-II (n = 71) with healthy urine specimens, the panel achieved AUCs of 0.90 (95% CI, 0.84-0.96) and 0.93 (95% CI, 0.84-1.00) in the training and validation datasets, respectively. In PDAC stage I-II and healthy samples with matching plasma CA19.9, the panel achieved a higher AUC of 0.97 (95% CI, 0.94-0.99) than CA19.9 (AUC = 0.88; 95% CI, 0.81-0.95, P = 0.005). Adding plasma CA19.9 to the panel increased the AUC from 0.97 (95% CI, 0.94-0.99) to 0.99 (95% CI, 0.97-1.00, P = 0.04), but did not improve the comparison of stage I-IIA PDAC (n = 17) with healthy urine.

Conclusions: We have established a novel, three-protein biomarker panel that is able to detect patients with early-stage pancreatic cancer in urine specimens.

©2015 American Association for Cancer Research.

Figures

Figure 1. Urine concentration of the candidate protein biomarkers

A, Scatter dot plots of LYVE1, REG1A, REG1B and TFF1 protein concentration (creatinine-normalised) analyzed by ELISA in healthy, chronic pancreatitis (CP) and pancreatic adenocarcinoma (PDAC) patients’ urine. Upper bars: Kruskal-Wallis test; ****: p<0.0001; ***: p<0.001. B, Statistical summary. Median and Interquartile range (IQR) of raw/creatinine-normalised data for the biomarkers, median and IQR of urine creatinine (mmol/L), as well as plasma CA19.9 (U/mL) by sample groups are shown.

Figure 2. Diagnostic performance of urine biomarkers in discriminating pancreatic adenocarcinoma patients from healthy controls

A, ROC curves of PDAC (n=143) versus healthy (n=59) subjects for individual creatinine-normalised urine biomarkers in the training set (70% of the data); B, ROC curves of PDAC versus healthy for the panel in the training set and in the independent validation set (30% of the data: PDAC n=49, healthy n=28); C, Summary table. AUC: area under the curve, SN: sensitivity, SP: specificity, with corresponding 95% Confidence Intervals (CI). SN and SP in the validation set are derived for optimal cutpoint determined in the training dataset. cnorm: creatinine-normalised, creat: creatinine.

Figure 3. Urine concentration of the three biomarkers in different stages of pancreatic adenocarcinoma

Scatter dot plots of urine LYVE1, REG1A, TFF1 protein concentration (creatinine-normalised) in urines of healthy (n=87) and pancreatic adenocarcinoma patients at different stages of disease development (I-IIA n=16, I-II n=71, III-IV n=77). Bars indicate median and IQR values. Upper bars: Kruskal-Wallis test; ****: p

Figure 4. Diagnostic performance of urine biomarkers in discriminating early pancreatic adenocarcinoma patients form healthy individuals

A, ROC curves of stages I-II PDAC (n=56) versus healthy (n=61) subjects for individual urine biomarkers in the training set (70% of the data); B, ROC curves of stage I-II PDAC versus healthy for the panel in the training set and in the independent validation set (30% of the data; PDAC n=15, healthy n=26); C, Summary table. AUC: area under the curve, SN: sensitivity, SP: specificity, with corresponding 95% Confidence Intervals (CI). SN and SP in the validation set are derived for optimal cutpoint determined in the training dataset. cnorm: creatinine-normalised, creat: creatinine.

Figure 5. Exploratory comparison of plasma CA19.9 and the urine biomarker panel in discriminating early pancreatic adenocarcinoma patients form healthy individuals

A, ROC curves of the biomarker panel with corresponding plasma CA19.9 alone and in combination comparing healthy urine (n=28), and urines from PDAC stages I-II, n=71 and I-IIA, n=16 (B). C, Summary table. AUC: area under the curve, SN: sensitivity, SP: specificity with 95% Confidence Interval (CI). SN and SP in the validation set were derived for optimal cutpoint determined in the training dataset.